V-RoAst A New Dataset for Visual Road Assessment

DOI

This is dataset used for V-RoAst A New Dataset for Visual Road Assessment (https://arxiv.org/html/2408.10872v2)The dataset used in this work is sourced from the ThaiRAP and was selected due to the availability of road assessment datasets adhering to the iRAP standard. The experiment includes 2,037 images (1600x1200 pixels) captured across Bangkok, Pathum Thani, and Phranakorn Sri Ayutthaya provinces, as illustrated in Figure 1 (please refer to the link). These images represent 519 road segments, with 1-4 images used to code each 100-meter segment. While iRAP datasets are typically not publicly available, this work will provide access to the ThaiRAP dataset, including both the images and their associated attributes, to support further research and development in road safety assessment. Each segment has 52 attributes classified by iRAP. However, the attributes have a different number of classes (codes) in (parenthesis), and the number of classes of each attribute used in this experiment is shown at the top of each bar in Figure 2 (please refer to the link). This dataset shows the imbalance of classes of attributes, in which there are 11 attributes with only one class. And some classes have less than 10 samples.

Identifier
DOI https://doi.org/10.5522/04/26520787.v1
Related Identifier HasPart https://ndownloader.figshare.com/files/48277894
Related Identifier IsSupplementedBy https://arxiv.org/html/2408.10872v2
Metadata Access https://api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:figshare.com:article/26520787
Provenance
Creator Jongwiriyanurak, Natchapon; Goo, June Moh; Zeng, Zichao; Wang, Xinglei; Haworth, James; Wang, Meihui; Ilyankou, Ilya
Publisher University College London UCL
Contributor Figshare
Publication Year 2024
Rights https://creativecommons.org/licenses/by-nc/4.0/
OpenAccess true
Contact researchdatarepository(at)ucl.ac.uk
Representation
Language English
Resource Type Figure; Image
Discipline Construction Engineering and Architecture; Engineering; Engineering Sciences